Capacitated vertiport and charging station location-allocation problem for air taxi operations with battery and fleet dispatching considerations: a case study of New York city

Abstract

Set to begin operations in the coming years, air taxi is an emerging ride-sharing aviation service that plans to commute millions of customers in metropolitan cities every day. However, existing literature has not holistically investigated the impact of the various strategic, tactical, and operations decisions pertaining to air taxi services (ATS). This research adopts a simulation-based framework to address the capacitated infrastructure location and demand allocation problems associated with ATS. Specifically, we determine the following decisions: (i) location and size of operating facilities and charging stations (strategic), (ii) air taxi fleet required to serve the expected demand at a specified service level (strategic), (iii) threshold minimum charge required for efficient air taxi operations (tactical), and (iv) real-time allocation of customer demand (operational). The proposed approach identifies the infrastructure locations using a clustering algorithm, and subsequently addresses the capacitated location-allocation problem for ATS by employing a simulation-based model. To test the effectiveness of the proposed approach, we consider a case study of New York City. We leverage the estimated air taxi demand and evaluate the proposed model by considering the weighted sum of fleet utilization and customer waiting time.

KEYWORDS:

• Air taxi
• advanced air mobility
• location-allocation problem
• fleet management
• simulation model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data used in this study was obtained from prior literature (Rajendran & Zack, 2019).